• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.6
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• pp.37-45
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• 2014

Ball valves are used as a key element in the process industries. The industrial development of valves has increased steadily, but continued improvement requires high design reliability and long service life. Currently, the development of high performance valves is not easy because of the lack of relevant technology in Korea. Valves are being imported at a level of up to 58 percent of the domestic market, which represents a value of almost 7 million US dollars. Therefore, in this work, the improvement of the design and performance of industrial valves has been studied in an attempt to achieve valves that will have longer service life and better output during operation. The structural stability was evaluated using the ANSYS FSI (Fluid-Structural Interaction) module. Moreover, to obtain maximum product reliability, torque analysis simulation was performed to compare and experimental results. The simulation results were used to predict the change in torque by changes in shape, thereby reducing the time and cost of manufacturing a number of prototypes for experimental validation.

• Journal of Information Technology Applications and Management
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• v.30 no.6
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• pp.91-111
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• 2023

This study aims to identify the influencing factors of intention to use cloud services using the SEM-ANN two-step approach. In previous studies of SEM-ANN, SEM presented R² and ANN presented MSE(mean squared error), so analysis performance could not be compared. In this study, R² and MSE were calculated and presented by SEM and ANN, respectively. Then, analysis performance was compared and feature importances were compared by sensitivity analysis. As a result, the ANN default model improved R² by 2.87 compared to the PLS model, showing a small Cohen's effect size. The ANN optimization model improved R² by 7.86 compared to the PLS model, showing a medium Cohen effect size. In normalized feature importances, the order of importances was the same for PLS and ANN. The contribution of this study, which links structural equation modeling to artificial intelligence, is that it verified the effect of improving the explanatory power of the research model while maintaining the order of importance of independent variables.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.5
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• pp.179-189
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• 2008

The object of this study is to develope a program with proposed numerical techniques for an optimal seismic control of structures using active tendon systems. Ricatti closed-loop algorithm has been applied to control the active tendon systems with time-delay problem. The optimal control is formulated as an optimization problem which is finding optimal weighting matrices by minimizing the quadratic performance index by SUMT. In order to find the optimal location of active tendons in structures, controllability index has been introduced. From numerical examples, the current optimal control technique with optimal location of tendons was suitable to control the seismic response of structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.1
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• pp.59-67
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• 2013

Complex-shaped tall building causes many structural challenges due to its structural characteristics regarding inclined members and complexed shape. This paper is aimed at development of design process using computational-platform which is effective design tool for responding frequent design changes, particularly as to overseas projects. StrAuto, a parametric structural modeling and optimizing system, provides the optimized alternatives according to design intent and realize a swift process converting a series of structural information necessary to nonlinear analytical models. The application of the process was to a 45-story hotel building in Ulanbator, Mongolia adopting shear wall and special moment frame with outrigger systems. To investigate the safety of lateral force resisting system against maximum considered earthquake(MCE), nonlinear response history analysis was conducted using StrAuto.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.3
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• pp.319-332
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• 2004

Due to their high strength to weight ratios and excellent durability, fiber reinforced polymer(FRP) is widely used in construction industries. In this paper, a shape optimum design of FRP bridge decks haying pultruded cellular cross-section is presented. In the problem formulation, an objective function is selected to minimize the volumes. The cross-sectional dimensions and material properties of the deck of FRP bridges are used as the design variables. On the other hand, deflection limits in the design code, material failure criteria, buckling load, minimum height, and stress are selected as the design constraints to enhance the structural performance of FRP decks. In order to efficiently treat the optimization process, the cross-sectional shape of bridge decks is assumed to be a tube shape. The optimization process utilizes an improved Genetic Algorithms incorporating indexing technique. For the structural analysis using a three-dimensional finite element, a commercial package(ABAQUS) is used. Using a computer program coded for this study, an example problem is solved and the results are presented with sensitivity analysis. The bridge consists of a deck width of 12.14m and is supported by five 40m long steel girders spaced at 2.5m. The bridge is designed to carry a standard DB-24 truck loading according to the Standard Specifications for Highway Bridges in Korea. Based on the optimum design, viable cross-sectional dimensions for FRP decks, suitable for pultrusion process are proposed.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.636-645
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• 2012

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• Computational Structural Engineering
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• v.9 no.2
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• pp.143-151
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• 1996

The optimal design for Electro-magnetic Launcher (EML : Rail Gun) considering structural and electrical constraints are presented. For the structure of EML under high pulsed currency, the cross section is minimized subject to maximum stress of each element(rail, side wall, ceramic, and steel) within allowable stress and preload limits. The electrical constraint is the effective ceramic thickness which prevents the eddy current effect reducing the performance of EML. The stress analysis and optimization procedure of 90mm EML is conducted with ANSYS Code. The optimal design under preload is reduced to 53% of area compared with optimal design without preload. In case of rail with arc angle .theta.=45.deg., the performance of EML is the best among the other rail arc angles. The optimal design for rail with arc angle .theta.=45.deg., results in the reduction of 9% of area and 10.4% of deformation compared with Fahrenthold's design. The optimal preload 59.8MPa is much lower than Fahrenthold's design(186MPa). The results show that the optimal design of EML meets the design requirements.

• Composites Research
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• v.36 no.6
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• pp.454-460
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• 2023

Recently, regulations on greenhouse gas emissions have been strengthened, and the International Maritime Organization (IMO) has been strengthening greenhouse gas regulations with a goal of net 'zero' emissions by 2050. In addition, in the shipbuilding/offshore sector, it is important to reduce operating costs, such as improving propulsion efficiency and lightening structures. In this regard, research is currently being conducted on topology optimization using 3D printed composite materials to satisfy structural lightness and high rigidity. In this study, three topology shapes (hexagonal, square, and triangular) were applied to the interior of a rudder, a ship structure, using 3D printed composite materials. Structural analysis was performed to determine the appropriate shape for the rudder. CFD analysis was performed at 10° intervals from 0° to 30° for each rudder angle under the condition of 8 knots, and the load conditions were set based on the CFD analysis results. As a result of the structural analysis considering the internal topology shape of the rudder, it was confirmed that the triangular, square, and hexagonal topology shapes have excellent performance. The rudder with a square topology shape weighs 78.5% of the rudder with a triangular shape, and the square topology shape is considered to superior in terms of weight reduction.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.326-330
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• 2007

Bumper back beam is one of the essential structural components of front-end module. It should be designed to withstand a minor bump in low-speed collision, 2.5 mph crash test for example. And weight reduction is always important problem in the design of almost all the parts in car for energy saving. So, the key issues in shape design of a bumper are weight reduction and the performance in 2.5mph crash test. In this study, a light weight and high performance bumper back beam model was developed using analytical approach based on mechanics and FE simulation together.